Mapping data:
Collecting and manipulating data

 

Collecting and manipulating data

Data are collected by sampling a population:

Population

Sample

Everybody in Santa Barbara County

1,000 respondents in a telephone poll, 20 questions

Precipitation in Colorado

450 rainfall "buckets" across the state

Africa

"Megaflyover", NGS, pictures every 20 seconds, georeferenced by lat/long

Ecology biodiversity

Transects and quadrats

From these samples we can extrapolate, or "go beyond" the sample data

Example: from the 450 rainfall gauges (points) we can make an isoline map of temperatures and "thread" the isolines between sample points. The location of the isoline is dependent on the point values.

This is called interpolation:

 

 

Some forms of extrapolation:

Interpolation

 

Inverse distance weighting (the simplest spatial interpolation method)

Earthworm prediction from IDW!

Spatial autocorrelation for prediction (Tobler's Law)

"Everything is related to everything else, but near things are more related" - Waldo Tobler, 1970

Spatial smoothing

Smoothing linear features

Tobler's "pycnophylactic method" for smoothing areas

Choropleth mapping (areal average, raises "boundary problem")

 

Geographically weighted regression (GWR)

 

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